Comparison of different instantaneous models of electron concentration height profiles at single location

Phys. Chem. Earth (C), Vol. 24, No. 4, pp. 385-388, 1999

0 1999 Elsevier Science Ltd

Pergamon

All rights reserved 1464-1917/99/$ - see front matter PII: S1464-1917(99)00017-3

Comparison of Different Instantaneous Models of Electron Cqncentration Height Profiles at Single Location I. Stanislawska,

Z. Zbyszyriski

and G. Juchnikowski

Space Research Centre PAS, 00-716 Warsaw, ul.Bartycka 18a, Poland Received 2 June 1998; revised 30 September 1998; accepted 30 September 1998

The comparison of different models of electron density height profile does not give a simple answer, because some of them can be better than other in a particular range of heights, or in particular situation. Some comparison criteria were proposed by Cander and Kecic (1994) and Singer et al. (1994). The validation of different models on a large digisonde data base was presented by Reinisch (1994). The test criteria usually take the different crucial points for different ionospheric layers. But the question which model is the best overall, particularly considering individual, instantaneous profile still persists. There are different opinions about the correctness of using instantaneous values - the values of ionospheric parameters in a single moment of time for an individual day - as input to models originally designed to compute monthly medians. The objection is caused by two facts: an ionospheric model uses several input parameters (more than one), and the median calculation means they can be from different time moments. This seems to lead to a very non-physical situation (Stanislawska et al., 1996). A more correct approach seems to be the use of a representative model which yields a profile averaged over a data set considered. This paper shows examples of profiles generated by different models during day time hours June 1995 at the Warsaw ionospheric station (52.13”N, 21.07”E) and discusses the usefulness ofthe average representative height profile of electron density for a given time of day.

Abstract. Three different models of electron concentration height profile have been compared to profiles obtained l?om ionograms at the Warsaw station. The electron density profiles are obtained from ionograms by inversion methods. These models use as an input the standard ionospheric characteristics. Some of the models are intended to compute monthly median profiles. To obtain the instantaneous profile the values of needed parameters are taken from the simultaneously constructed instantaneous maps of ionospheric parameters. For instantaneous maps construction, two techniques are used: the kriging technique with modifications concerning ionospheric behaviour, where deviations of measurements from monthly median maps are used, and a fitting method where median maps are updated with measurements. The comparison is done for the COST 238 PRIME height profile model, a local model based on a modified Rush model, and a model where an artificial neural network technique is aaplied to time series of profiles. The usefulness of the average representative height profile constructed from a set of instantaneous profiles is discussed. 0 1999 Elsevier Science Ltd. All rights reserved.

1 Introduction The model of electron density profile below the F2 peak is important for radio wave propagation applications. In practice it is important to adopt the best, the most convenient and suitable method of updating the electron density profile in order to obtain a profile at a requested geographic location. It is a crucial problem for radiocommunication forecasting. The use of the profile is more convenient than the use of maps of separate ionospheric parameters. The comparison of experimental and model profiles is not straightforward, even for individual cases where both are available. Especially for radiocommunication purposes, for planning and operational use, the discussion is still open which model to use. Correspondence

2 Models of Electron Concentration Height Profile Three models of electron concentration height profile have been compared: the height profiles of electron concentration up to the maximum of F2 layer from ionograms obtained at the Warsaw ionospheric station (52.13”N, 2 1.07”E) with the use of an algorithm developed based $I the Titheridge method (1985), the COST 23 8 PRIME height profile model (Radicella and Zhang, 1995), a simply derived, but sufficiently realistic N(h) ionospheric model while a local

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I. Stanislawska et al.: Different Instantaneous Models of Electron Concentration Height Profiles

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Fig.2. The set of profiles (thin lines) and their representative profiles (thick lines) for 1OUTfor PRIME, Rush-type model, NN - model and measurements

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I. Stanislawska ec al.: Different Instantaneous Models of Electron Concentration Height Profiles model is based on a modified Rush model (Rush et al., 1974, Stanislawska et al., 1991) and a model based on time series of ionograms and artificial neural network technique - NN (Stanislawska, 1998). Since the models taken into consideration are intended for radiocommunication purposes, their important feature is simplicity; the parameters needed to obtain the results must be easy to access. The input parameters for the PRIME model are the following: foF2, foF1, foE and M(3000)F2, for the Rush model: foE, foF2, M(300O)F2 and YmF2 (FZ-region semithickness) and for the NN model: Iinin, h’E, foE, foF1 and foF2. First two models: PRIME and the Rush-type have been developed to compute monthly medians. The values of the parameters needed to compute the instantaneous profiles can be obtained from simultaneously constructed instantaneous maps of ionospheric parameters (Bradley, 1995) or directly from measurements at the considered point. 2.1 Ionogram Modelling Every measured ionogram has been described by 28 variables including 11 points for which the frequency and the heights are defined and the following 5 parameters: fmin, h’E, foE, foF1 and foF2and the hour. These 6 parameters have been chosen as the crucial points to every ionogram. The artificial neural network technique has been used to obtain the full ionogram (28 variables). The most important feature of the neural network is its ability to elaborate on-line forecasting, made on the basis of the statistical data collected within previous period of the operation of the system. These 6 parameters are the input to the neural network. This way the neuralnetwork serves as the universal approximator or vector quantizer which allows to associate the given 6 parameters and the hour with some prototypes from the past that were typical at that kind of conditions. In the process of training the ionograms from daily circumstances of one month - June 1995 - has been chosen. For training only 50% of available ionograms has been taken. Based on this information an accurate forecast can be prepared. In this approach the feedforwardmultilayer structure has been applied (Ossowski, 1994). The architecture proposed is based on a multilayer perceptron with changed metric and directional minimalisation of the optimal value of the learning coefficient.

was computed with the use of inversion method by Titheridge (1985) applied also to the measured ionograms.

3 Profile Comparison and Conclusions A comparison of the profiles for 13 June 5 UT, 14 June 5 UT, 7 June 10 UT, 7 June 15 UT is presented in Fig.1 The comparison suggests that the most promising results are given by the neural network technique, but this technique is not mature yet and needs further development, particularly for night time hours. The curves from NN follow the real data fairly well for both quiet and disturbed days. Not surprisingly, the PRIME and Rush-type models applied to instantaneous situations differ significantly from real the data because they were developed to compute monthly median however, PRIME only. For that type of application, performs quite well. It is not clear how to define a monthly median profile. Instead we define a ‘representative’ profile. The average representative profile (ARP) construction has been introduced and developed by Reinish and Huang (1996). The authors follow this idea because it seems it has more advantages and it could be very useful in profile modelling

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Fig. 3. The comparison of representative profiles for 10 UT. P _ PRIME, R - Rush-typemodel,N -Neural networkapproachand D - data

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The accuracy of the ionograms from July 1995 computed with the use of a net trained for the preceeding month (June 1995) is presented in Table 1. The profile for such ionograms

Fig.4. Sample oftbe representative PRIME model (PR) and PRIME model

on medians (PM) for 15 UT. For comparison the representative profile constructed for real protiles (DR) is presented

I. Stanislawska et al.: Different Instantaneous Models of Electron Concentration Height Profiles

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A simple method ofaveraging ofprofiles has been elaborated. Every profile is divided into three parts grouped separately: f?om fmin to foE, from foE to foF1 and from foFl to foF2. Within every group the profile is first normalized to unity, first in heights and then in densities. Then the averaging is done with the step of 0.05 and the resulting profile is spread to the previous scale with the use of the average value of parameters considered.

data, the monthly median values are taken as input parameters for NN model (Fig.5). In the same figure the PRIME and Rush-type model with median values are presented, as well as the experimental profiles at the same hour for particular day profile. Also in this case the NN technique seems to give better results. The presented NN approach might be very useful not only for forecasting but also for filling time and height gaps between measurements in the Warsaw location and in the surrounding area defined by the correlation radius of ionospheric parameters. However, the training data base supplemented with profiles from other locations might allow to produce the profiles at considerably larger area. This technique seems promising, but it is not complete yet and needs further studies, particularly for night time hours. A special stress will be put to the validation with the profiles obtained with the use of other also satellite techniques. The model is under development. Acknowledgements. The authors thank to profB.Reinisch from Center for

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Fig.5. Sample of the results for June 1975 1OUT when as an input to the models medians arc taken. PM - PRIME, RM - Rush-type model, NM Neural network approach and DR - representative profile for the measurements

This technique has been applied to the following set of profiles: ionogram derived, PRIME, Rush-type and NN for day time hours in June 1995. The regular form of representative profiles is illustrated in Figure 2. The figure presents also the set ofprofiles andtheirrepresentative profile for 10UT. Figure 3 shows a comparison of four representative profiles. In the case of ionogram-derived profiles the shape of the representative profile is in agreement with the expectation. This suggests that the method is correct and can be applied also to the profile models. Since the PRIME and Rush-type models were developed to compute medians ionospheric parameters and they returned averaged profiles the representative profile based on results they returned from instantaneous data should not differ very much fi-om the profile computed from medians Such comparison is presented in Figure 4 for the PRIME model. Indeed the two PRIME curves agree very well, but still they differ from the representative model developed fiorn the measurements. The lack of some input parameters can be also resolved by using the predicted monthly median values, as it is done for the PRIME and Rush-type models. When the construction of the instantaneous maps is not possible because of lack of the

Atmospheric Research, University of Massachusetts, Lowell, USA for helpful discussion.. This work is partly supported by the Polish Committee of Scientific Research Grant No.2PO3CO1108.

References BradleyP.A., PRIME (Prediction andRetrospecfive Ionospheric Modeiling over Europe), Final Report, Commission ofthe European Communities, ECSC-EEC-EAEC, Brussels, 1995. Gander, Lj.R. and Kecic, Z.J., Comparison of different N(h) profiles with mid-latitude ionospheric observations, Adv. Space Rex, 14, l&91-94, 1994.

Radicella, S.M. and Zhang, M.-L., The Improved DGR Analytical Model of Electron Density Height Profile and Total Electron Content in the Ionosphere, Annali di Geofisica, XLYVIII, 1, 35, 1995. Ossowski, S., Sieci neuronowe, OWPW, Warszawa(in polish), 1994. Reinisch, B.W., Anderson, D.,Gamache,R.R.,Huang,X., Chen, CF., and Decker, D.T., Validation of ionospheric models with measured electron density profiles, AC&.Space Res., 14, 12, 67-70, 1994. Reinish, B.W. and Huang, X., Low latitude digisonde measurements and comparison with IRI, Adv. Space Rex, 18, 6, 5-12, 1996. Singer, W., Weiss, J., and Bremer, J., Comparing the improved di Giovanni/Radicella model with sounding-based electron density profiles and with the IRI model, Adv. Space Res., 14, 12, 83-86, 1994. Stanislawska, I., Klos, Z., and Stasiewicz, K., Local Models of the Ionosphere Based upon Data from Miedzeszyn Station, Proceedings of the IIIPRME Workshop, Rome, January 1991, 161-164, 1991. Stanislawska, I., Klos, Z , and Juchnikowski, G., Further studies on electron density height profile modelling, Proc. of Solar-Terrestrial Predictions Workshop_V,Hitachi, January 1996,391-394, 1996. Stanislawska, I., The neural network technique applied to the analysis ofthe ionograms at Warsaw ionospheric station, Acfa Geophysics Polonica, 1998 (submitted). Titheridge, J.E., Ionogram Analysis with the Generalized Program POLAN, UAG-93. University of Auckland, New Zeland, 1985.